SF-MCP

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It discloses that this is a read operation ('fetches the service document'), but lacks details on authentication behavior, rate limits, error handling, or what 'service document' entails. It adds some context about being a discovery tool but misses key behavioral traits for a tool with authentication parameters.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded with the core purpose in the first sentence. The Args and Returns sections are structured for clarity. Minor redundancy exists (e.g., 'SuccessFactors' repeated), but overall it's efficient with zero wasted sentences.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (6 params, authentication, discovery function) and no annotations, the description does well: it explains purpose, parameters, and return values. However, with an output schema present, the Returns section is somewhat redundant. It lacks details on error cases or operational constraints, leaving minor gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must fully compensate. It successfully adds meaning for all 6 parameters: explaining what each represents (e.g., 'SAP data center code', 'Environment type'), providing examples ('DC55', 'preview'), noting requirements ('required'), and detailing the category filter with options and default. This goes well beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('List all available OData entities') and resources ('SuccessFactors instance'), distinguishing it from sibling tools that focus on specific data queries (e.g., query_odata, get_employee_profile). It explicitly identifies this as a 'discovery tool' for understanding available data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool ('helps users understand what data is available to query'), but does not explicitly state when not to use it or name specific alternatives. It implies usage for discovery before querying, but lacks explicit exclusions or comparisons to siblings like query_odata.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.